Search AI Products and News

AI startup Luma recently announced on X that it has open-sourced a new image model pretraining technique called Inductive Moment Matching (IMM). This breakthrough technology has garnered significant attention for its efficiency and stability, considered a major advancement in the generative AI field. According to X user linqi_zhou, IMM is a novel generative paradigm capable of stable training from scratch with a single model and single objective, surpassing existing methods in both sampling efficiency and sample quality.

At the World Economic Forum held in Davos, Switzerland, artificial intelligence (AI) became a hot topic, with many industry leaders emphasizing that employee retraining is crucial for realizing the transformative potential of AI. Rishad Premji, Executive Chairman of Wipro Limited, noted in an interview with NDTV that the successful adoption of AI is closely tied to the retraining of employees. This insight highlights a strategic necessity for company executives and ERP leaders — organizations must

The World Economic Forum recently released the "Future of Jobs Report 2025," revealing an intriguing contradiction: while artificial intelligence (AI) is seen as a technology that will replace certain jobs, global companies are more inclined to retrain existing employees rather than resort to layoffs. The report surveyed 1,000 companies worldwide, and the results showed that about 41% of companies plan to cut positions that AI can handle, while 77% focus more on training current employees in AI skills. This trend highlights that many companies wish to adapt to AI through retraining.

Researchers from Stanford University and the University of California, Berkeley conducted an experiment to explore the consequences of retraining AI image generation models using images generated by the AI itself. The experiment utilized the Stable Diffusion (SD) model and selected high-quality facial images from the FFHQ dataset for automatic generation. The results showed that after retraining, the AI model produced highly distorted images. This distortion originated not only from the text prompts used for retraining but also persisted even when retraining was done solely with real images.

The team from Peking University and the Hong Kong University of Science and Technology made a big splash with a new training method that has achieved GPT-4 level performance with an 8B-sized medical expert model. This is no small feat, and they have also introduced a new concept, "stability gap," to explain certain phenomena observed during the continuous pre-training of large language models.Image Source Note: The image is generated by AI, and the image is provided by Midjourney, an image autho